Method and system for user group determination, churn identification and content selection

Abstract

One or more computing devices, systems, and/or methods are provided. In an example, purchase data associated with users may be determined. The purchase data may be indicative of purchases by users from entities. The purchase data may be analyzed to determine purchase metrics associated with the users. The purchase metrics may be analyzed to determine sets of groups of users associated with the entities. One or more groups of users, of the sets of groups of users, that include the user may be determined. Content may be selected for presentation via a first device associated with the first user based upon the one or more groups of users.

What is claimed is: 
     
         1 . A method, comprising:
 determining purchase data comprising:
 first purchase data indicative of purchases by a first user from first entities; and 
 second purchase data indicative of purchases by a second user from second entities; 
   analyzing the purchase data to determine:
 a first set of purchase metrics associated with the first user; and 
 a second set of purchase metrics associated with the second user; 
   analyzing purchase metrics, comprising the first set of purchase metrics and the second set of purchase metrics, to determine:
 a first set of groups of users associated with a first entity based upon first purchase metrics, of the purchase metrics, associated with the first entity; and 
 a second set of groups of users associated with a second entity based upon second purchase metrics, of the purchase metrics, associated with the second entity; 
   identifying customer churn of the first user from the first entity to the second entity based upon a determination that the first user is in:
 an inactive group of users of the first set of groups of users; and 
 an active group of users of the second set of groups of users; and 
   selecting, based upon the identification of the customer churn of the first user from the first entity to the second entity, content for presentation via a first device associated with the first user.   
     
     
         2 . The method of  claim 1 , wherein:
 the first set of purchase metrics comprises recency metrics comprising:
 a first recency metric associated with one or more first purchases, by the first user, from a third entity of the first entities; and 
 a second recency metric associated with one or more second purchases, by the first user, from a fourth entity of the first entities. 
   
     
     
         3 . The method of  claim 1 , wherein:
 the first set of purchase metrics comprises frequency metrics comprising:
 a first frequency metric associated with one or more first purchases, by the first user, from a third entity of the first entities; and 
 a second frequency metric associated with one or more second purchases, by the first user, from a fourth entity of the first entities. 
   
     
     
         4 . The method of  claim 1 , wherein:
 the first set of purchase metrics comprises monetary metrics comprising:
 a first monetary metric associated with one or more first purchases, by the first user, from a third entity of the first entities; and 
 a second monetary metric associated with one or more second purchases, by the first user, from a fourth entity of the first entities. 
   
     
     
         5 . The method of  claim 1 , wherein the determining the purchase data comprises:
 analyzing messages associated with the first user to identify a first message indicative of a first purchase by the first user from a third entity of the first entities.   
     
     
         6 . The method of  claim 1 , wherein:
 the identification of the customer churn of the first user from the first entity to the second entity is based upon a determination that the first entity and the second entity are associated with an entity category.   
     
     
         7 . The method of  claim 1 , wherein the determining the first set of groups of users comprises:
 clustering users into the first set of groups of users based upon the first purchase metrics associated with the first entity.   
     
     
         8 . The method of  claim 7 , wherein:
 the clustering comprises performing density-based clustering.   
     
     
         9 . The method of  claim 1 , comprising:
 receiving a request for content associated with the first device, wherein the selecting the content for presentation via the first device is performed in response to receiving the request for content; and   transmitting the content to the first device.   
     
     
         10 . The method of  claim 1 , wherein the first set of purchase metrics comprises:
 recency metrics comprising:
 a first recency metric associated with one or more first purchases, by the first user, from a third entity of the first entities; and 
 a second recency metric associated with one or more second purchases, by the first user, from a fourth entity of the first entities; 
   frequency metrics comprising:
 a first frequency metric associated with the one or more first purchases, by the first user, from the third entity; and 
 a second frequency metric associated with the one or more second purchases, by the first user, from the fourth entity; and 
   monetary metrics comprising:
 a first monetary metric associated with the one or more first purchases, by the first user, from the third entity of the first entities; and 
 a second monetary metric associated with the one or more second purchases, by the first user, from the fourth entity of the first entities. 
   
     
     
         11 . A computing device comprising:
 a processor; and   memory comprising processor-executable instructions that when executed by the processor cause performance of operations, the operations comprising:
 determining purchase data comprising:
 first purchase data indicative of purchases by a first user from first entities; and 
 second purchase data indicative of purchases by a second user from second entities; 
 
 analyzing the purchase data to determine:
 a first set of purchase metrics associated with the first user, wherein the first set of purchase metrics comprises first recency metrics, first frequency metrics and first monetary metrics; and 
 a second set of purchase metrics associated with the second user, wherein the second set of purchase metrics comprises second recency metrics, second frequency metrics and second monetary metrics; 
 
 analyzing purchase metrics, comprising the first set of purchase metrics and the second set of purchase metrics, to determine sets of groups of users associated with entities comprising a first entity and a second entity, wherein the sets of groups of users comprises:
 a first set of groups of users associated with the first entity, wherein the first set of groups of users is based upon first purchase metrics, of the purchase metrics, associated with the first entity; and 
 a second set of groups of users associated with the second entity, wherein the second set of groups of users is based upon second purchase metrics, of the purchase metrics, associated with the second entity; 
 
 determining one or more first groups of users, of the sets of groups of users, comprising the first user; and 
 selecting, based upon the one or more first groups of users, content for presentation via a first device associated with the first user. 
   
     
     
         12 . The computing device of  claim 11 , the operations comprising:
 receiving, from a second device, targeting information associated with the content, wherein:
 the targeting information is indicative of one or more second groups of users to which the content is targeted; and 
 the selection of the content for presentation via the first device is based upon a determination that one or more groups of users, of the one or more first groups of users, are comprised in the one or more second groups of users indicated by the targeting information. 
   
     
     
         13 . The computing device of  claim 11 , wherein the determining the first set of groups of users comprises:
 clustering users into the first set of groups of users based upon the first purchase metrics associated with the first entity.   
     
     
         14 . The computing device of  claim 13 , wherein:
 the clustering comprises performing density-based clustering.   
     
     
         15 . The computing device of  claim 11 , the operations comprising:
 receiving a request for content associated with the first device, wherein the selecting the content for presentation via the first device is performed in response to receiving the request for content; and   transmitting the content to the first device.   
     
     
         16 . A non-transitory machine readable medium having stored thereon processor-executable instructions that when executed cause performance of operations, the operations comprising:
 determining activity data comprising:
 first activity data indicative of user activity of a first user with internet resources associated with first entities; and 
 second activity data indicative of user activity of a second user with internet resources associated with second entities; 
   analyzing the activity data to determine:
 a first set of activity metrics associated with the first user; and 
 a second set of activity metrics associated with the second user; 
   analyzing activity metrics, comprising the first set of activity metrics and the second set of activity metrics, to determine:
 a first set of groups of users associated with a first entity based upon first activity metrics, of the activity metrics, associated with the first entity; and 
 a second set of groups of users associated with a second entity based upon second activity metrics, of the activity metrics, associated with the second entity; 
   identifying user churn of the first user from the first entity to the second entity based upon a determination that the first user is in:
 an inactive group of users of the first set of groups of users; and 
 an active group of users of the second set of groups of users; and 
   selecting, based upon the identification of the user churn of the first user from the first entity to the second entity, content for presentation via a first device associated with the first user.   
     
     
         17 . The non-transitory machine readable medium of  claim 16 , wherein:
 the first set of activity metrics comprises recency metrics comprising:
 a first recency metric associated with user activity of the first user with one or more first internet resources associated with a third entity of the first entities; and 
 a second recency metric associated with user activity of the first user with one or more second internet resources associated with a fourth entity of the first entities. 
   
     
     
         18 . The non-transitory machine readable medium of  claim 16 , wherein:
 the first set of activity metrics comprises frequency metrics comprising:
 a first frequency metric associated with user activity of the first user with one or more first internet resources associated with a third entity of the first entities; and 
 a second recency metric associated with user activity of the first user with one or more second internet resources associated with a fourth entity of the first entities. 
   
     
     
         19 . The non-transitory machine readable medium of  claim 16 , wherein the determining the first set of groups of users comprises:
 clustering users into the first set of groups of users based upon the first activity metrics associated with the first entity.   
     
     
         20 . The non-transitory machine readable medium of  claim 19 , wherein:
 the clustering comprises performing density-based clustering.